Brain electrical microstates in subjects with panic disorder

Brain electrical microstates represent spatial configurations of scalp recorded brain electrical activity and are considered to be the basic elements of stepwise processing of information in the brain. In the present study, the hypothesis of a temporo-limbic dysfunction in panic disorder (PD) was tested by investigating the topographic descriptors of brain microstates, in particular the one corresponding to the Late Positive Complex (LPC), an event-related potential (ERP) component with generators in these regions. ERPs were recorded in PD patients and matched healthy subjects during a target detection task, in a central (CC) and a lateral condition (LC). In the CC, a leftward shift of the LPC microstate positive centroid was observed in the patients with PD versus the healthy control subjects. In the LC, the topographic descriptor of the first microstate showed a rightward shift, while those of both the second and the fourth microstate, corresponding to the LPC, revealed a leftward shift in the PD patients versus the healthy control subjects. These findings indicate an overactivation of the right hemisphere networks involved in early visual processing and a hypoactivation of the right hemisphere circuits involved in LPC generators in PD. In line with this interpretation, the abnormal topography of the LPC microstate, observed in the CC, was associated with a worse performance on a test exploring right temporo-hippocampal functioning. Topographical abnormalities found for the LPC microstate in the LC were associated with a higher number of panic attacks, suggesting a pathogenetic role of the right temporo-hippocampal dysfunction in PD.

Prestimulus EEG microstates influence visual event-related potential microstates in field maps with 47 channels

The influence of the immediate prestimulus EEG microstate (sub-second epoch of stable topography/map landscape) on the map landscape of visually evoked 47-channel event-related potential (ERP) microstates was examined using the frequent, non-target stimuli of a cognitive paradigm (12 volunteers). For the two most frequent prestimulus microstate classes (oriented left anterior-right posterior and right anterior-left posterior), ERP map series were selectively averaged. The post-stimulus ERP grand average map series was segmented into microstates; 10 were found. The centroid locations of positive and negative map areas were extracted as landscape descriptors. Significant differences (MANOVAs and t-tests) between the two prestimulus classes were found in four of the ten ERP microstates. The relative orientation of the two ERP microstate classes was the same as prestimulus in some ERP microstates, but reversed in others. — Thus, brain electric microstates at stimulus arrival influence the landscapes of the post-stimulus ERP maps and therefore, information processing; prestimulus microstate effects differed for different post-stimulus ERP microstates.

Hemispheric lateralization patterns and psychotic experiences in healthy subjects

The hypothesis that psychotic experiences in healthy subjects are associated with a dysfunction of the right hemisphere is supported by some, but not all, available studies. Differences in gender composition of study samples may explain in part the divergent findings. The present study was carried out in 42 healthy, right-handed university students. Scores on the Schizophrenia and Paranoia scales of the Minnesota Multidimensional Personality Inventory-2 were used in correlation analyses and to define a High- and a Low-Psychotic group. Brain Electrical Microstates and Low Resolution Electromagnetic Tomography (LORETA) source analyses of the auditory P300 (P3a and P3b) components of the event-related potential, as well as a battery of neuropsychological tests, were used to assess hemispheric functioning. Scores on the Paranoia scale were positively associated with a leftward shift of the P3a topographic descriptors in females but not in males. When comparing High-Psychotic and Low-Psychotic females, a leftward shift of P3a descriptors and an increased cortical activation in left fronto-temporal areas were observed in the High-Psychotic group. Our results demonstrated gender-related differences in the pattern of hemispheric imbalance associated with psychotic experiences in healthy subjects.

MQN-Mapplet: Visualization of Chemical Space with Interactive Maps of DrugBank, ChEMBL, PubChem, GDB-11, and GDB-13

The MQN-mapplet is a Java application giving access to the structure of small molecules in large databases via color-coded maps of their chemical space. These maps are projections from a 42-dimensional property space defined by 42 integer value descriptors called molecular quantum numbers (MQN), which count different categories of atoms, bonds, polar groups, and topological features and categorize molecules by size, rigidity, and polarity. Despite its simplicity, MQN-space is relevant to biological activities. The MQN-mapplet allows localization of any molecule on the color-coded images, visualization of the molecules, and identification of analogs as neighbors on the MQN-map or in the original 42-dimensional MQN-space. No query molecule is necessary to start the exploration, which may be particularly attractive for nonchemists. To our knowledge, this type of interactive exploration tool is unprecedented for very large databases such as PubChem and GDB-13 (almost one billion molecules). The application is freely available for download at www.gdb.unibe.ch.

Understanding diversity of hepatic metabolism and related adaptations in the early lactating dairy cow.

The onset of lactation in dairy cows represents a major metabolic challenge that involves large adaptations in glucose, fatty acid, and mineral metabolism to support lactation and to avoid metabolic dysfunction. The complex system of adaptation can differ considerably between cows, and may have a genetic base. In the present review, the variation in adaptive reactions in dairy cows is discussed. In these studies, the liver being a key metabolic regulator for understanding the variation in adaptive performance of the dairy cow was the main focus of research. Liver function was evaluated through gene expression measurements; to explain the associated phenotypic variability and to identify descriptors for metabolic robustness in dairy cows. Hence, the identified genes involved act as a connecting link between the genotype encoded on the DNA and the phenotypic expression of the target factors at a protein level. The integration of phenotypic data, including gene expression profiles, and genomic data will facilitate a better characterization of the complex interplay between these levels, and will improve the genetic understanding necessary to unravel a certain trait or multi-trait such as metabolic robustness in dairy cows.

Sparse representation based action and gesture recognition

In this paper we present a solution to the problem of action and gesture recognition using sparse representations. The dictionary is modelled as a simple concatenation of features computed for each action or gesture class from the training data, and test data is classified by finding sparse representation of the test video features over this dictionary. Our method does not impose any explicit training procedure on the dictionary. We experiment our model with two kinds of features, by projecting (i) Gait Energy Images (GEIs) and (ii) Motion-descriptors, to a lower dimension using Random projection. Experiments have shown 100% recognition rate on standard datasets and are compared to the results obtained with widely used SVM classifier.

Index-Oriented Methodologies for Landslide Consequence Analysis: An Application to a Mountain Community in the French Alps

Consequence analysis is a key aspect of anchoring assessment of landslide impacts to present and long-term development planning. Although several approaches have been developed over the last decade, some of them are difficult to apply in practice, mainly because of the lack of valuable data on historical damages or on damage functions. In this paper, two possible consequence indicators based on a combination of descriptors of the exposure of the elements at risk are proposed in order to map the potential impacts of landslides and highlight the most vulnerable areas. The first index maps the physical vulnerability due to landslide; the second index maps both direct damage (physical, structural, functional) and indirect damage (socio-economic impacts) of landslide hazards. The indexes have been computed for the 200 km2 area of the Barcelonnette Basin (South French Alps), and their potential applications are discussed.

Effects of forest management on ground-dwelling beetles (Coleoptera; Carabidae, Staphylinidae) in Central Europe are mainly mediated by changes in forest structure

Forest management is known to influence species diversity of various taxa but inconsistent or even contrasting effects are reported for arthropods. Regional differences in management as well as differences in regional species pools might be responsible for these inconsistencies, but, inter-regional replicated studies that account for regional variability are rare. We investigated the effect of forest type on the abundance, diversity, community structure and composition of two important ground-dwelling beetle families, Carabidae and Staphylinidae, in 149 forest stands distributed over three regions in Germany. In particular we focused on recent forestry history, stand age and dominant tree species, in addition to a number of environmental descriptors. Overall management effects on beetle communities were small and mainly mediated by structural habitat parameters such as the cover of forest canopy or the plant diversity on forest stands. The general response of both beetle taxa to forest management was similar in all regions: abundance and species richness of beetles was higher in older than in younger stands and species richness was lower in unmanaged than in managed stands. The abundance ratio of forest species-to-open habitat species differed between regions, but generally increased from young to old stands, from coniferous to deciduous stands and from managed to unmanaged stands. The response of both beetle families to dominant tree species was variable among regions and staphylinid richness varied in the response to recent forestry history. Our results suggest that current forest management practices change the composition of ground-dwelling beetle communities mainly by favoring generalists and open habitat species. To protect important forest beetle communities and thus the ecosystem functions and services provided by them, we suggest to shelter remaining ancient forests and to develop near-to-nature management strategies by prolonging rotation periods and increasing structural diversity of managed forests. Possible geographic variations in the response of beetle communities need to be considered in conservation-orientated forest management strategies.

A Logical Descriptor for Regular Languages via Stone Duality

In this paper we introduce a class of descriptors for regular languages arising from an application of the Stone duality between finite Boolean algebras and finite sets. These descriptors, called classical fortresses, are object specified in classical propositional logic and capable to accept exactly regular languages. To prove this, we show that the languages accepted by classical fortresses and deterministic finite automata coincide. Classical fortresses, besides being propositional descriptors for regular languages, also turn out to be an efficient tool for providing alternative and intuitive proofs for the closure properties of regular languages.

Prediction of Trabecular Bone Anisotropy from Quantitative Computed Tomography using Supervised Learning and a Novel Morphometric Feature Descriptor

Patient-specific biomechanical models including local bone mineral density and anisotropy have gained importance for assessing musculoskeletal disorders. However the trabecular bone anisotropy captured by high-resolution imaging is only available at the peripheral skeleton in clinical practice. In this work, we propose a supervised learning approach to predict trabecular bone anisotropy that builds on a novel set of pose invariant feature descriptors. The statistical relationship between trabecular bone anisotropy and feature descriptors were learned from a database of pairs of high resolution QCT and clinical QCT reconstructions. On a set of leave-one-out experiments, we compared the accuracy of the proposed approach to previous ones, and report a mean prediction error of 6% for the tensor norm, 6% for the degree of anisotropy and 19◦ for the principal tensor direction. These findings show the potential of the proposed approach to predict trabecular bone anisotropy from clinically available QCT images.

Stereological estimation of particle shape and orientation from volume tensors

In the present paper, we describe new robust methods of estimating cell shape and orientation in 3D from sections. The descriptors of 3D cell shape and orientation are based on volume tensors which are used to construct an ellipsoid, the Miles ellipsoid, approximating the average cell shape and orientation in 3D. The estimators of volume tensors are based on observations in several optical planes through sampled cells. This type of geometric sampling design is known as the optical rotator. The statistical behaviour of the estimator of the Miles ellipsoid is studied under a flexible model for 3D cell shape and orientation. In a simulation study, the lengths of the axes of the Miles ellipsoid can be estimated with CVs of about 2% if 100 cells are sampled. Finally, we illustrate the use of the developed methods in an example, involving neurons in the medial prefrontal cortex of rat.

Tree architecture in a Bornean lowland rain forest: intraspecific and interspecific patterns

Intraspecific and interspecific architectural patterns were studied for eight tree species of a Bornean rain forest. Trees 5--19 m tall in two 4-ha permanent sample plots in primary forest were selected, and three light descriptors and seven architectural traits for each tree were measured. Two general predictions were made: (1) Slow growing individuals (or short ones) encounter lower light, and have flatter crowns, fewer leaf layers, and thinner stems, than do fast growing individuals (or tall ones). (2) Species with higher shade-tolerance receive less light and have flatter crowns, fewer leaf layers, and thinner stems, than do species with lower shade-tolerance. Shade-tolerance is assumed to decrease with maximum growth rate, mortality rate, and adult stature of a species.